• Nicole Papaioannou Lugara

Four Data Starting Points for Every Training Problem

Data is only as good as as the analysis. That's probably something you already know, since you're living in the era of Big Data.


That's why, even though I'm not an "Analyst," as a L&D professional, it's important to know how to define data needs, collect data, analyze it, and most importantly, take action as a result of that data.


But many instructional designers and eLearning developers feel lost when it comes to data. The sheer amount of it can be overwhelming. Getting access to data can be intimidating. It's one of the reasons I began the From Data to Design program (which, by the way, is currently open for enrollment through May 26).


So today, I want to look at some easy ways to use data when it comes to solving training problems.


Note: Not all training problems are actually training problems, even when the client so.


Let's start at the beginning.


What is data?


Data is literally just information. Data collection may have gotten a little fancier with AI and unique data visualization tools, but in reality, you don't need a computer to gather data. Data doesn't have to be "big data" to be valuable.


Data is the observations you make.


Data is the problem your client tells you about.


Data is the number of people who got a question wrong on a quiz.


Data is everywhere.


You can collect data through conversations, through surveys, through assessments. The possibilities are endless.


As a L&D professional, data can be used to help you make design choices or to evaluate success.


The Four Starting Points


In general, I suggest checking out these four data points when you're trying to figure how to fix a training problem.


The course (or learning experience) - This is the actual training event, whether it's an eLearning, vILT, Slack channel, or something else entirely. When it comes to time to "fix" a training problem, it's good to know what came before.


The source refers to the source materials-- documents, manuals, SME guidance, etc.


The people are any of the people involved in delivering and taking the course (or learning experience).


The system are those used to deliver the training and potentially to assess learner progress.


It's true there are tons of ways to think about and gather data, but if you're looking for a way to get started when it comes to training, these four will set you off in the right direction.


And again, this is for when you know it's training problem. If you think it's management, culture, or some other non-training-related issue, these four data points may not make a huge impact on your problem-solving process.


See how it works with the use cases below.


Use Case #1: "Our training is not working."


There are so many reasons training might not work, and often, they have nothing to do with training. But for the sake of this use case, let's pretend it's actually a failure of the existing training product.


Something just isn't clicking between the eLearning module and on the job performance. And it's software training done with an interactive simulation.


You have to figure out what's not working in the course and fix it. You do know they're making specific errors on the job, but not what's wrong with the training.


What do you do to identify the issue?


Here's how you might use the four starting points.

  1. Go to the course. This is probably the most obvious place to start-- reviewing the content. Is it delivered in a way that is clear? Is it easy to discern critical information from the stuff that's just good-to-know. When SMEs are asked to perform ID roles, ineffective delivery is common.

  2. Go to the source. Sometimes, the content doesn't align with the source materials. In this case you might ask things like: Is the right version of the software presented? Are the user manuals reflecting the same processes as the training?

  3. Go to the people. Ask real learners why the concept is challenging. Keep in mind, they may not realize it's challenging or want to admit it is.

  4. Go to the system. If you have advanced data reporting from the delivery systems (e.g., using xAPI to see where students are clicking), you can start to pinpoint where students are struggling or dropping off. Where are students most frequently clicking the wrong thing, for example? Where are students dropping off or taking breaks?


Addressing these four areas would make it easier to start updating-- or potentially fully redesigning-- the learning experience to be more effective.


Use Case # 2: "We need to make this training more engaging."


Ah yes, "engagement," one of the biggest buzzwords in business these days. So many times, these requests come with other quips like, "can we add some gamification or something?"


In this case, let's say the client noticed that their training videos aren't being watched, and that's a problem because they spent 6 months making over 100 them! They're supposed to help customer service reps manage their responses to different scenarios. Now, they want you to watch all 100 videos and come up with some ways to make them better.


What data might you want before making your recommendations?


Again, looking at the four starting points...


  1. Go to the course.... err, videos. Again, ask yourself, are these videos instructionally sound? Since there's over 100, I'd also ask "are they search friendly?"

  2. Go to the source. Are the scenarios relevant and relatable? That would be the #1 question I'd have. Where is the content being pulled from?

  3. Go to the people. Assuming the people want these videos and would find them useful, you could start asking questions like: What questions do you want these videos to help you answer? What motivates you to do your job well?

  4. Go to the system. If your client is hosting video on something that offers advanced reporting, you might be able to gather data that tells you what videos are being watched most frequently vs least frequently, where students are dropping offer, and where they're rewinding.


It's on you.


Full disclosure: most of my clients aren't asking these questions or offering me this data. I have to propose data collection and ask for what I need. And sometimes, I have to make a case for it because they don't take me at my word.


Don't be afraid to consult clients. If you've been hired for your expertise, you owe it to them to provide it.



Want to learn more about how to identify needs and turn out impactful learning solutions? Check out From Data to Design, the 9-week program designed to help you level up from order taker to strategic partner.


Enrollment for the Spring 201 cohort ends May 26.



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